Vol. 13 No. 1(J) (2021)

The objective of this study was to analyze the money demand function for Zambia for the period 1978 – 2018 using annual time series data. The study employed the Gregory Hansen cointegration technique. The study also employed Hendry’s General to Specific technique to estimate the error correction model by obtaining a parsimonious model. The results of the Gregory Hansen test confirmed the presence of a cointegrating relationship and selected the GH-2 model as the most plausible model with a level shift and a trend. The results also endogenously determined 1994 as the break year in the money demand function. Other interesting results obtained by the study suggest that inflation and interest rate are the robust determinants of real money demand both in the short and long run. Furthermore, unlike many other developing countries, the results show that money is a necessity in Zambia. The other interesting results suggested by the study are that the financial sector reforms of 1994 diminished the demand for real money; however, the positive time trend suggests that there has been an increase in real money holdings over time in Zambia. The low-interest elasticity of money demand also potentially compromises the effectiveness of money supply as a monetary policy tool for economic stabilization. The results of the CUSUM and CUSUMSQ confirm the stability of the money demand function in Zambia.

Empathy is expected to correlate with pro-social attitude s, but what effect does empathy have on judgments of distributive fairness? In our study, we found that participants with higher empathy scores on the Interpersonal Reactivity Index (IRI) were more likely to: (a) favor the use of egalitarian distribution when the joint effort is involved, and (b) deem overly self-interested or opportunistic behavior unfair. Female participants were more consistent in the exercise of moral judgments across diverse scenarios. Furthermore, empathy has several dimensions (e.g., perspective-taking or empathetic concern) and we observed that they interacted with gender and the nature of the hypothetical problem differently in some cases. Although the findings of the study are not counterintuitive, it has identified some avenues for further explorations and highlighted some potential methodological shortcomings of the IRI as a measure of empathetic traits.

Recently, the analysis of communication has gained attention in experimental research. One important question is whether certain types of communication affect decisions differently than others. In this regard, Houser & Xiao (2011) present an approach for the classification of natural language messages. The primary limitation of their approach is its limited applicability to large message datasets. Therefore, Penczynski (2019) extends the methodological instruments by applying a machine learning classifier to experimental communication data. This is accompanied by the problem of a dearth of machine learning knowledge among experimenters. Hence, this paper presents an approach that employs a publicly available machine learning text analysis application. This makes it possible to analyze larger datasets based on small training datasets classified beforehand by human evaluators. As a first step, I use primary communication data reported by Charness and Dufwenberg (2006) to generate both training and test datasets. Following this approach, I am able to substantially replicate the original classification results obtained by Charness and Dufwenberg. The second step again involves messages from Charness and Dufwenberg as training data, while I take messages from a related trust game published by Deck et al. (2013) as a test, dataset. Promisingly, I am also able to replicate the classification results obtained by the external evaluators, as reported by Deck et al. The findings suggest that machine learning can be used to analyze large message datasets, both if the artificial intelligence is trained with data from the very same experiment and if it is trained with message data from a comparable experiment.

The mining sector has been the cornerstone of economic growth in Zimbabwe hence funding becomes very crucial to resuscitate the economy. The study aimed to assess the funding mechanisms for the mining sector of Zimbabwe and the effect of these on the performance of the sector. A quantitative study was carried out in the mining sector. The research findings showed that respondents pointed out that the funding mechanisms used in the mining sector of Zimbabwe are project finance, finance by private equity, public bonds and loans from banks and other financial institutions. It was also revealed that over and above available mechanisms, investment in the mining sector is being influenced by Interest rate, Business economic empowerment policies, bank lending criteria and Technical information, simultaneously. Furthermore, the study established that the mining sector needs skilled and technical staff, Technical information, banks’ lending criteria and Capital markets to get funding from investors. It was derived that, investment in the mining sector will increase production, product quality and profitability which in turn lead to infrastructural development. In addition, it is envisaged that funding will result in mining exports increase at the same time that new technologies are being introduced and the GDP is rising. Owing to the focus being exclusively on the funding of the mining sector, the study also recommended further studies on other factors, besides funding, that are affecting the performance of the sector.

A mixed strategy, a strategy of unpredictable actions, is applicable to business, politics, and sports. Playing mixed strategies, however, poses a challenge, as the game theory involves calculating probabilities and executing random actions. I test i.i.d. hypotheses of the mixed strategy Nash equilibrium with the simplest experiments in which student participants play zero-sum games in multiple iterations and possibly figure out the optimal mixed strategy (equilibrium) through the games. My results confirm that most players behave differently from the Nash equilibrium prediction for the simplest 2x2 zero-sum game (matchingpennies) and 3x3 zero-sum game (e.g., the rock-paper-scissors game). The results indicate the need to further develop theoretical models that explain a non-Nash equilibrium behavior.